NOAA National Climatic Data Center

weather_df = 
  rnoaa::meteo_pull_monitors(c("USW00094728", "USC00519397", "USS0023B17S"),
                      var = c("PRCP", "TMIN", "TMAX"), 
                      date_min = "2017-01-01",
                      date_max = "2017-12-31") %>%
  mutate(
    name = recode(id, USW00094728 = "CentralPark_NY", 
                      USC00519397 = "Waikiki_HA",
                      USS0023B17S = "Waterhole_WA"),
    tmin = tmin / 10,
    tmax = tmax / 10,
    month = lubridate::floor_date(date, unit = "month")) %>%
  select(name, id, date, month, everything())

Column

Chart A

weather_df %>%
  mutate(text_label = str_c("tmax: ", tmax, "\ntmin: ", tmin)) %>% 
  plot_ly(
    x = ~tmax, y = ~tmin, type = "scatter", mode = "markers",
    color = ~name, text = ~text_label, alpha = 0.5)

## Warning: Ignoring 15 observations

Column

Chart B

weather_df %>%
  mutate(text_label = str_c("tmax: ", tmax, "\ntmin: ", tmin)) %>% 
  plot_ly(
   y = ~tmax, color = ~name, type = "box",colors = "Set1")

## Warning: Ignoring 3 observations

Chart C

weather_df %>% 
  filter((tmax-tmin) > 10) %>% 
  count(name) %>% 
  plot_ly(x = ~name, y = ~n, color = ~name, type = "bar")